Alternatives and similar repositories for efficient-transformers

Users that are interested in efficient-transformers are comparing it to the libraries listed below

• onnx / neural-compressor
  Model compression for ONNX
  ☆97Updated 11 months ago
• NVlabs / EfficientDL
  ☆34Updated 4 months ago
• google-ai-edge / ai-edge-quantizer
  AI Edge Quantizer: flexible post training quantization for LiteRT models.
  ☆72Updated this week
• mlcommons / mobile_app_open
  Mobile App Open
  ☆63Updated this week
• Libraries-Openly-Fused / cvGPUSpeedup
  A faster implementation of OpenCV-CUDA that uses OpenCV objects, and more!
  ☆53Updated last month
• Qualcomm-AI-research / transformer-quantization
  ☆205Updated 3 years ago
• Qualcomm-AI-research / FP8-quantization
  ☆163Updated 2 years ago
• quic / cloud-ai-sdk
  Qualcomm Cloud AI SDK (Platform and Apps) enable high performance deep learning inference on Qualcomm Cloud AI platforms delivering high …
  ☆66Updated 2 months ago
• meta-pytorch / multipy
  torch::deploy (multipy for non-torch uses) is a system that lets you get around the GIL problem by running multiple Python interpreters i…
  ☆181Updated 2 months ago
• facebookresearch / fairring
  Fairring (FAIR + Herring) is a plug-in for PyTorch that provides a process group for distributed training that outperforms NCCL at large …
  ☆65Updated 3 years ago
• GATECH-EIC / SuperTickets
  [ECCV 2022] SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning
  ☆20Updated 3 years ago
• LukasHedegaard / pytorch-benchmark
  Easily benchmark PyTorch model FLOPs, latency, throughput, allocated gpu memory and energy consumption
  ☆107Updated 2 years ago
• gpu-mode / triton-tutorials
  ☆15Updated 5 months ago
• fastmachinelearning / qonnx
  QONNX: Arbitrary-Precision Quantized Neural Networks in ONNX
  ☆161Updated this week
• meta-pytorch / tokenizers
  C++ implementations for various tokenizers (sentencepiece, tiktoken etc).
  ☆39Updated this week
• ankan-ban / llama_cu_awq
  llama INT4 cuda inference with AWQ
  ☆55Updated 9 months ago
• wangsiping97 / FastGEMV
  High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.
  ☆117Updated last year
• leimao / Nsight-Systems-Docker-Image
  Nsight Systems In Docker
  ☆20Updated last year
• foundation-model-stack / foundation-model-stack
  🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.
  ☆215Updated this week
• vllm-project / compressed-tensors
  A safetensors extension to efficiently store sparse quantized tensors on disk
  ☆180Updated this week
• jundaf2 / INT8-Flash-Attention-FMHA-Quantization
  ☆158Updated 2 years ago
• DeMoriarty / custom_matmul_kernels
  Customized matrix multiplication kernels
  ☆57Updated 3 years ago
• facebookresearch / NasRec
  NASRec Weight Sharing Neural Architecture Search for Recommender Systems
  ☆31Updated last year
• ultralytics / thop
  Profile PyTorch models for FLOPs and parameters, helping to evaluate computational efficiency and memory usage.
  ☆59Updated this week
• IntelLabs / FP8-Emulation-Toolkit
  PyTorch extension for emulating FP8 data formats on standard FP32 Xeon/GPU hardware.
  ☆111Updated 10 months ago
• meta-pytorch / superblock
  A block oriented training approach for inference time optimization.
  ☆33Updated last year
• ahennequ / cuda-tensorcores-register-mapping
  ☆19Updated 3 years ago
• hisrg / SNPE
  Snapdragon Neural Processing Engine (SNPE) SDKThe Snapdragon Neural Processing Engine (SNPE) is a Qualcomm Snapdragon software accelerate…
  ☆35Updated 3 years ago
• tlc-pack / libflash_attn
  Standalone Flash Attention v2 kernel without libtorch dependency
  ☆112Updated last year
• ShishirPatil / poet
  ML model training for edge devices
  ☆167Updated 2 years ago